| | ---
|
| | language: en
|
| | tags:
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| | - healthcare
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| | - stroke-prediction
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| | - medical
|
| | license: mit
|
| | datasets:
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| | - stroke-prediction
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| | model-index:
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| | - name: Stroke Risk Prediction Model
|
| | results:
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| | - task:
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| | type: binary-classification
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| | name: stroke prediction
|
| | metrics:
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| | - type: accuracy
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| | value: 0.95
|
| | - type: f1
|
| | value: 0.82
|
| | ---
|
| |
|
| | # Stroke Risk Prediction Model
|
| |
|
| | This model predicts the likelihood of a person experiencing a stroke based on various health and demographic features.
|
| |
|
| | ## Model Description
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| |
|
| | The model is a Random Forest classifier trained on healthcare data to predict stroke risk and categorize individuals into risk levels.
|
| |
|
| | ### Input
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| |
|
| | The model accepts the following features:
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| | - **gender**: Male, Female, Other
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| | - **age**: Age in years (numeric)
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| | - **hypertension**: Whether the patient has hypertension (0: No, 1: Yes)
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| | - **heart_disease**: Whether the patient has heart disease (0: No, 1: Yes)
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| | - **ever_married**: Whether the patient has ever been married (Yes/No)
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| | - **work_type**: Type of work (Private, Self-employed, Govt_job, children, Never_worked)
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| | - **Residence_type**: Type of residence (Urban/Rural)
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| | - **avg_glucose_level**: Average glucose level in blood (mg/dL)
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| | - **bmi**: Body Mass Index
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| | - **smoking_status**: Smoking status (formerly smoked, never smoked, smokes, Unknown)
|
| |
|
| | ### Output
|
| |
|
| | The model outputs:
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| | - **probability**: Numerical probability of stroke (0-1)
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| | - **prediction**: Risk category (Very Low Risk, Low Risk, Moderate Risk, High Risk, Very High Risk)
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| | - **stroke_prediction**: Binary prediction (0: No stroke, 1: Stroke)
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| |
|
| | ### Limitations and Biases
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| |
|
| | - The model was trained on a dataset that may have demographic limitations
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| | - Performance may vary across different population groups
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| | - This model should be used as a screening tool only and not as a definitive medical diagnosis
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| |
|
| | ## Usage
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| |
|
| | ```python
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| | import requests
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| |
|
| | API_URL = "https://api-inference.huggingface.co/models/Abdullah1211/ml-stroke"
|
| | headers = {"Authorization": "Bearer YOUR_API_TOKEN"}
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| |
|
| | def query(payload):
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| | response = requests.post(API_URL, headers=headers, json=payload)
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| | return response.json()
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| |
|
| | data = {
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| | "gender": "Male",
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| | "age": 67,
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| | "hypertension": 1,
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| | "heart_disease": 0,
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| | "ever_married": "Yes",
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| | "work_type": "Private",
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| | "Residence_type": "Urban",
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| | "avg_glucose_level": 228.69,
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| | "bmi": 36.6,
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| | "smoking_status": "formerly smoked"
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| | }
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| |
|
| | output = query(data)
|
| | ``` |
